Forward Model Parameters Research Articles

SGEMS-UQ: An uncertainty quantification toolkit for SGEMS

While algorithms and methodologies to study uncertainty in the Earth Sciences are constantly evolving, there is currently no free integrated software that allows the general practitioners access to these developments. This paper presents SGEMS-UQ, a plugin for the SGEMS platform, that is used to perform distance-based uncertainty analysis on geostatistical simulations, and the resulting forward transfer function responses used in subsurface modeling and engineering. A versatile XML-derived dialect is defined for communicating with external programs that reduces the need for ad-hoc linking of codes, and a relational database system is implemented to automate many of the steps in data mining the spatial and forward model parameters. Through a graphical user interface, one can map a set of realizations and forward transfer function responses into a multidimensional scaling (MDS) space where visualization utilities, and clustering techniques are available. Once mapped in the MDS space, the user can explore linkage between simulation parameters and forward transfer function responses using a module based on a SQL database. Consideration is given to the use of software engineering paradigms and design patterns to produce a code-base that is manageable, efficient, and extensible for future applications, while being scalable to work with large datasets. Finally, we illustrate the versatility of the code-base on an application of modeling uncertainty in reservoir forecasts for an oil reservoir in the West Coast of Africa.

Implementation of the Daytime Cloud Optical and Microphysical Properties Algorithm (DCOMP) in PATMOS-x

AbstractThis paper describes the daytime cloud optical and microphysical properties (DCOMP) retrieval for the Pathfinder Atmosphere’s Extended (PATMOS-x) climate dataset. Within PATMOS-x, DCOMP is applied to observations from the Advanced Very High Resolution Radiometer and employs the standard bispectral approach to estimate cloud optical depth and particle size. The retrievals are performed within the optimal estimation framework. Atmospheric-correction and forward-model parameters, such as surface albedo and gaseous absorber amounts, are obtained from numerical weather prediction reanalysis data and other climate datasets. DCOMP is set up to run on sensors with similar channel settings and has been successfully exercised on most current meteorological imagers. This quality makes DCOMP particularly valuable for climate research. Comparisons with the Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 dataset are used to estimate the performance of DCOMP.

Retrieval procedure for time-resolved near-infrared tissue spectroscopy based on the optimal estimation method

We propose the use of a retrieval procedure for time-resolved near-infrared tissue spectroscopy based on the ‘optimal estimation’ method. The aim of this retrieval method is to obtain an improved estimate of the target parameters compared with standard nonlinear least-squares routines, since the inverse problem dedicated to retrieve the optical properties of tissue is ill posed. A priori information on target and forward model parameters is used, so that a larger number of target parameters can be retrieved, and/or a better accuracy and precision can be achieved on the retrieved target parameters. The procedure has been tested on time-resolved simulated experiments generated, using solutions of the diffusion equation and with solutions of the radiative transfer equation reconstructed with Monte Carlo simulations. The results obtained show that, by using a priori information on target parameters, we have a smaller difference between retrieved values and true values, and lower retrieved error bars. Similarly, a more correct estimate of the errors of the forward model parameters improves the retrieval of the target parameters.

Coupled hydrogeophysical inversion of electrical resistances and inflow measurements for topsoil hydraulic properties under constant head infiltration

ABSTRACTAccurate estimation of topsoil hydraulic properties is important for understanding water flow and solute transport in the vadose zone. Coupled hydrogeophysical inversion schemes that enable the use of multiple geophysical and hydrological data for the estimation of soil hydraulic properties have recently been proposed. In these coupled inversion schemes, a hydrological model describing the process under investigation is coupled to a forward geophysical model and hydraulic parameters are directly estimated from geophysical measurements. While these schemes provide a suitable platform for the integration of multiple geophysical and hydrological data, efficient methods to combine these data types for improved parameter estimation still warrant investigation. In this study, we investigated the feasibility of estimating three topsoil Mualem‐van Genuchten parameters from the fusion of inflow and electrical resistance measurements obtained under constant head infiltration. In addition to using only inflow or electrical resistances, we investigated three methods of combining these data for improved estimation of topsoil hydraulic parameters. Our results show that using inflow alone does not provide a unique solution to the inverse problem. Better results are obtained with the additional use of electrical resistance data. We show that successful data fusion within the coupled hydrogeophysical inversion framework depends on the choice of an appropriate objective function. We obtained the best data fusion results with an objective function defined as the sum of the root mean square error of both data types normalized by the standard deviation of the respective measurements. In this case, the inverted hydraulic parameters were very comparable to reference values obtained from a multi‐step outflow experiment carried out with undisturbed soil cores from the experimental site. It is concluded that the coupled hydrogeophysical inversion frame‐work is a promising tool for non‐invasive near‐surface hydrological investigations.

External forward shock origin of high-energy emission for three gamma-ray bursts detected by Fermi

We analyze the >100MeV data for 3 GRBs detected by Fermi (GRBs 080916C, 090510, 090902B) and find that these photons were generated via synchrotron emission in the external forward shock. We arrive at this conclusion by four different methods as follows. (1) We check the light curve and spectral behavior of the >100MeV data, and late time X-ray and optical data, and find them consistent with the closure relations for the external forward shock radiation. (2) We calculate the expected external forward shock synchrotron flux at 100MeV, and it matches the observed flux value. (3) We determine the external forward shock model parameters using the >100MeV data, and with these we calculate the expected X-ray and optical fluxes at late times (hours to days after the burst) and find these to be in good agreement with the observed data. (4) We calculate the external forward shock model parameters using only the late time X-ray, optical and radio data and from these estimate the expected flux at >100 MeV at the end of the sub-MeV burst (and at subsequent times) and find that to be entirely consistent with the high energy data obtained by Fermi/LAT. The ability of a simple external forward shock, to fit the entire data from the end of the burst (1-50s) to about a week, covering more than eight-decades in photon frequency provides compelling confirmation of the external forward shock synchrotron origin of the >100MeV radiation from these Fermi GRBs. Moreover, the parameters determined in points (3) and (4) show that the magnetic field required in these GRBs is consistent with shock-compressed magnetic field in the circum-stellar medium with pre-shocked values of a few tens of micro-Gauss.

Beamformer analysis of fetal MEG data with intermittent nonstationarity

Event Abstract Back to Event Beamformer analysis of fetal MEG data with intermittent nonstationarity Jack McCubbin1*, Pamela Murphy1, Maureen Ware1, Eric Siegel1, Hari Eswaran1, Jiri Vrba2, Curtis Lowery1 and Hubert Preissl3 1 UAMS, United States 2 UAMS, Elekta Neuromag, United States 3 U. Tuebingen , UAMS, United States MEG recordings from subjects such as fetus, newborn, or child may have intermittent nonstationarity. In the case of fetal MEG, the data is characterized by frequent subject movements, complex near-field interference structure, and limited duration records. Beamformer provides a good spatial filter for the near-field interferers however the method assumes stationary data and static forward model parameters. The poor knowledge of origin for the fetal head model sphere has been addressed by scanning over a grid of origins as well as model source grids within each model sphere. Recently, the effect of subject movement has been minimized by using a sliding analysis window along the full record duration and selecting statistically significant clusters of activity in the statistical parametric map for each window using random field theory. The expected reduction of latency with increasing gestational age was observed with that processing scheme for a series of low-risk pregnancies, providing a validation of the beamformer method. The procedure has since been refined by the addition of an MCG interference leakage criterion and replacement of the manual latency estimation with a semi-automated method to reduce operator bias. The processing was applied to a series of high-risk fetal MEG records which included fetal ultrasound surveillance data. We found that both umbilical artery and middle cerebral artery Doppler measures were correlated with visual flash-evoked latency estimates. Since both Doppler measures and latency are normally correlated with fetal development, these results provide additional evidence for reliable latency estimates from beamformer processing and may lead to a new measure for direct fetal neurological development to complement existing surveillance measures. In addition, this processing strategy may be adaptable to other situations with intermittent nonstationarity. Conference: Biomag 2010 - 17th International Conference on Biomagnetism , Dubrovnik, Croatia, 28 Mar - 1 Apr, 2010. Presentation Type: Poster Presentation Topic: Fetal and neonatal biomagnetism Citation: McCubbin J, Murphy P, Ware M, Siegel E, Eswaran H, Vrba J, Lowery C and Preissl H (2010). Beamformer analysis of fetal MEG data with intermittent nonstationarity. Front. Neurosci. Conference Abstract: Biomag 2010 - 17th International Conference on Biomagnetism . doi: 10.3389/conf.fnins.2010.06.00132 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Mar 2010; Published Online: 24 Mar 2010. * Correspondence: Jack McCubbin, UAMS, Little Rock, United States, mccubbin@telus.net Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jack McCubbin Pamela Murphy Maureen Ware Eric Siegel Hari Eswaran Jiri Vrba Curtis Lowery Hubert Preissl Google Jack McCubbin Pamela Murphy Maureen Ware Eric Siegel Hari Eswaran Jiri Vrba Curtis Lowery Hubert Preissl Google Scholar Jack McCubbin Pamela Murphy Maureen Ware Eric Siegel Hari Eswaran Jiri Vrba Curtis Lowery Hubert Preissl PubMed Jack McCubbin Pamela Murphy Maureen Ware Eric Siegel Hari Eswaran Jiri Vrba Curtis Lowery Hubert Preissl Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Assessing the SMOS Soil Moisture Retrieval Parameters With High-Resolution NAFE'06 Data

The spatial and temporal invariance of Soil Moisture and Ocean Salinity (SMOS) forward model parameters for soil moisture retrieval was assessed at 1-km resolution on a diurnal basis with data from the National Airborne Field Experiment 2006. The approach used was to apply the SMOS default parameters uniformly over 27 1-km validation pixels, retrieve soil moisture from the airborne observations, and then to interpret the differences between airborne and ground estimates in terms of land use, parameter variability, and sensing depth. For pastures (17 pixels) and nonirrigated crops (5 pixels), the root mean square error (rmse) was 0.03 volumetric (vol./vol.) soil moisture with a bias of 0.004 vol./vol. For pixels dominated by irrigated crops (5 pixels), the rmse was 0.10 vol./vol., and the bias was -0.09 vol./vol. The correlation coefficient between bias in irrigated areas and the 1-km field soil moisture variability was found to be 0.73, which suggests either 1) an increase of the soil dielectric roughness (up to about one) associated with small-scale heterogeneity of soil moisture or/and 2) a difference in sensing depth between an L-band radiometer and the in situ measurements, combined with a strong vertical gradient of soil moisture in the top 6 cm of the soil.

Early kinematic history of the Goban Spur rifted margin derived from a new model of continental breakup and sea-floor spreading initiation

Abstract Deformation of continental lithosphere leading to breakup and the initiation of sea-floor spreading can be described in terms of an upwelling divergent flow field within the continental lithosphere and asthenosphere. A new model (SfMargin) of rifted continental margin formation using this upwelling divergent flow field has been developed that successfully predicts lithosphere depth-dependent stretching and mantle exhumation at rifted margins. The kinematics of this flow field has important consequences for the bathymetric (subsidence) and thermal history of continental margin lithosphere. We apply the new model to a profile through the Goban Spur on the eastern Atlantic continental margin. Forward modelling yields parameter values describing the kinematics of the flow field leading to continental breakup and sea-floor spreading initiation that are consistent with the known amagmatic history of this margin. We employ a grid search method to systematically explore model parameter space and provide an assessment of the sensitivity of the model to the kinematic flow field parameter values. The preferred forward model parameters coincide with low values of misfit with respect to observed present-day bathymetry and free air gravity anomalies. Our results reveal the early kinematic history of the Goban Spur margin as characterized by a ratio of upwelling rate to half-spreading rate of unity, consistent with that expected for the initiation of sea-floor spreading at a non-volcanic rifted margin and only a modest amount of prebreakup lithospheric stretching (β=1.5). These results conform with recent observations of depth-dependent stretching and serpentinized mantle exhumation at this amagmatic rifted continental margin.

MARC: A code for the retrieval of atmospheric parameters from millimeter-wave limb measurements

A new data analysis software is presented that has been developed for the retrieval of atmospheric minor constituents from limb-sounding observations made in the millimeter and sub-millimeter spectral regions. The code, which is called MARC (Millimetre-wave Atmospheric-Retrieval Code), has been designed to analyze the observations of the MARSCHALS (Millimetre-wave Airborne Receivers for Spectroscopic CHaracterisation in Atmospheric Limb-Sounding) instrument which operates on the M-55 stratospheric aircraft. The main objective of the analysis of MARSCHALS observations will be to assess long-wave measurement capabilities for the study of the upper troposphere and lower stratosphere regions. The key questions will be the accuracy and spatial resolution that can be achieved by long-wave measurements in presence of clouds and horizontal gradients. MARC performs a global-fit multi-target retrieval, in which optimal estimation is used and errors of the forward model parameters are taken into account for the definition of the cost function minimized in the retrieval. With these features it is easy to use the variables of the problem as either forward model constant parameters or retrieved unknowns with minimum impact on the stability of the retrieval. MARC can perform a wide spectral-band analysis of the observations without a selection of the analyzed channels, and the retrieval process provides an error budget of the retrieved unknowns that includes both the forward model errors and the measurement errors. The error budget obtained in this way is smaller than that obtained when accounting a posteriori for the systematic errors. The new combination of the retrieval features makes possible an efficient and optimal exploitation of the information content of the observations.

A new approach to the retrieval of surface properties from earthshine measurements

Instruments such as the MODIS and MISR radiometers on EOS AM-1, and POLDER on ADEOS have been deployed for the remote sensing retrieval of surface properties. Typically, retrieval algorithms use linear combinations of semi-empirical bidirectional reflectance distribution function (BRDF) kernels to model surface reflectance. The retrieval proceeds in two steps; first, an atmospheric correction relates surface BRDF to top-of-atmosphere (TOA) reflectances, then regression is used to establish the linear coefficients used in the kernel combination. BRDF kernels may also depend on a number of physical or empirical non-linear parameters (e.g. ocean wind speed for a specular BRDF); such parameters are usually assumed known. A major source of error in this retrieval comes from lack of knowledge of planetary boundary layer (PBL) aerosol properties. In this paper, we present a different approach to surface property retrieval. For the radiative transfer simulations, we use the discrete ordinate LIDORT model, which has the capability to generate simultaneous fields of radiances and weighting functions in a multiply scattering multi-layer atmosphere. Surface–atmosphere coupling due to multiple scattering and reflection effects is treated in full; the use of an atmospheric correction is not required. Further, it is shown that sensitivities of TOA reflectances to both linear and non-linear surface BRDF parameters may be established directly by explicit analytic differentiation of the discrete ordinate radiative transfer equations. Surface properties may thus be retrieved directly and conveniently from satellite measurements using standard non-linear fitting methods. In the fitting for BRDF parameters, lower-boundary aerosol properties can either be retrieved as auxiliary parameters, or they can be regarded as forward model parameter errors. We present examples of simulated radiances and surface/aerosol weighting functions for combinations of multi-angle measurements at several different wavelengths, and we perform some examples of self-consistent non-linear fitting to demonstrate feasibility for this kind of surface property retrieval.

Late Carboniferous tectonic subsidence in South Wales: implications for Variscan basin evolution and tectonic history in SW Britain

Detailed stratigraphic data have been used to backstrip seven sections from the Carboniferous South Wales coal basin. Resulting tectonic subsidence curves for the interval 319–305 Ma (Namurian–Westphalian D) are convex‐up, indicating increasing subsidence rate with time, with rates between 130 and 250 m Ma −1 , suggesting a foreland basin setting. Forward modelling of subsidence due to flexural loading in front of a propagating orogenic wedge shows that an orogenic load migrating in a north‐northeasterly direction across SW England between 319 and 305 Ma could have generated the backstripped subsidence patterns. Sensitivity tests show that while many of the forward model parameters are poorly constrained, and the model results non‐unique, backstripped subsidence patterns allow reasonable constraint on the different model cases, so that model predictions can be treated as one possibility in a limited range. The predicted load evolution is consistent with current knowledge of tectonic and stratigraphic features of SW England. These results suggest that subsidence in other Late Carboniferous UK basins may also have been influenced by flexure due to a propagating orogenic load.

Parameter estimation using multifrequency range-dependent acoustic data in shallow water

The estimation of all forward model parameters—geometric, geoacoustic, and ocean sound speed—by the inversion of acoustic field observations is considered. The data was taken at a mildly range-dependent shallow water site in the Mediterranean Sea. The inversion is based on data from a vertical array and carried out using information at multiple frequencies. Global optimization using a directed Monte Carlo search based on genetic algorithms and the Bartlett objective function is used. All geometric parameters are well determined, a range-dependent geoacoustic model is determined, and the ocean sound speed is estimated. Comparisons of the observed pressure field as a function of depth and the predicted field show good agreement. The use of observations at multiple frequencies provides considerable stability for the estimated parameters. Optimization of only geometric and geoacoustic parameters in a range-independent environment is found to be satisfactory at the lower frequencies (165–175 Hz), but for the higher frequencies (325–335 Hz) optimization of additional parameters by inclusion of either a range-dependent forward model or the ocean-sound-speed profile seems essential for successful inversion.

Inversion of broadband multitone data from the Yellow Shark experiments

The estimation of forward model parameters—geometric, geoacoustic, and ocean sound-speed—by the inversion of acoustic field observations is considered. During autumn ’94 and spring ’95 an exhaustive set of broadband acoustic data and environmental data was obtained over a shallow-water area in the Mediterranean Sea [Hermand etal., ‘‘The Yellow Shark Broadband Inversion Experiments’’ (to be published)]. In this paper, inversion results of a mildly range-dependent transect southeast of the Island of Elba are presented. The inversion is carried out from multitone data (in the frequency band 200–1600 Hz) received on a 62-m vertical array from a fixed acoustic projector deployed at different ranges (4.5–15 km). Hydrographic data measured during the acoustic transmissions and coring and seismic profiling of the sediments along the acoustic track are utilized to control and verify the inversion process. Global optimization through a directed Monte Carlo search based on genetic algorithms and the Bartlett objective function is applied. All geometric parameters are well determined and also a range-dependent geoacoustic model and the ocean sound-speed profile are estimated. The use of observations at multiple frequencies provides considerable stability for the estimated parameters.

Inversion for geometric and geoacoustic parameters in shallow water: Experimental results

Experimental results on the estimation of both geometric and geoacoustic parameters in shallow water are presented. Genetic algorithms are used for estimation of the forward model parameters; the estimated parameters are then used by a standard Bartlett processor for source localization. A stationary source at a range of 5.6 km and a moving source at ranges from 5.8–7.7 km were successfully localized in range and depth using a single frequency Bartlett processor. The results indicate that global estimation of the forward model parameters significantly improves source localization performance.